Spatial smoothing process and device for dark regions of an image

ABSTRACT

The invention relates to a process, to a device for smoothing dark regions of images and to a coding system,—a noise level is associated with each image and a luminance value is associated with each pixel,—a threshold value is calculated,—at least two values delimiting a smoothing range are defined,—for each current pixel, the luminance of the pixel is compared with the said values,—if the luminance of the current pixel lies in a smoothing range, the luminance of several pixels in an analysis window is compared with the said values,—if the luminance of certain pixels lies in the same range as the value of the luminance of the current pixel, the value of the luminance of the current pixel is modified as a function of the said threshold values.

[0001] The present invention relates to a process and to a device forspatial smoothing as well as to a corresponding coding system.

[0002] It relates to the noise reduction techniques applied to digitalvideo signals. These techniques are generally applied to digital videoimages taking the form of a matrix of samples; each sample is composedof a luminance signal and, for a colour signal, of a chrominance signal.

[0003] The acquisition of video image sequences is still today largelycarried out in analogue form so that the images, once acquired andpossibly transmitted and stored in analogue formats, exhibit anappreciable share of noise in their content. Once digitized, theseimages are also often subjected to storage/editing operations which, intheir turn, introduce noise, this time of a digital nature. Finally, animage sequence generally undergoes a succession of transformationsresulting in spatio-temporal noise of a highly random nature.

[0004] To obtain high-performance operation, the noise reduction methodscall upon recursive filtering which considers the very high temporalcorrelation of the images of a video sequence. These filters are veryeffective but have the drawback of making the noise homogeneous andhence of giving the final result a “dirty window pane” effect. This isespecially visible in the dark regions of the image.

[0005] The invention therefore relates to the homogenization of the darkregions of an image based on the amplitude of the luminance of thepixels of this image.

[0006] U.S. Pat. No. 4,962,426 filed in the name of the company HitachiLimited discloses noise reducing systems which use the amplitude of theluminance. Such systems use the amplitude of the luminance to increasethe stringency of the noise reducing filter, in the analogue domain.

[0007] Such systems are therefore not adapted for homogenizing the darkregions of an image having undergone a deterioration as they passthrough a recursive filter. Moreover, such systems do not allow variablesmoothing of an image and are not adapted to operate in the domain ofdigital images.

[0008] The invention therefore proposes a smoothing process based on anoise estimate and on the value of the luminance of each current pointwhich makes it possible to obtain good image quality, while considerablyreducing the negative effects alluded to above.

[0009] Accordingly, the invention concerns a process for smoothing darkregions of an image sequence having undergone temporal filtering, anoise level being associated with each image, a luminance value beingassociated with each pixel of an image. According to the invention:

[0010] at least one predetermined, so-called threshold value, iscalculated as a function of the noise level of the image and the zerovalue is added to the calculated values,

[0011] at least two predetermined values are defined which delimit atleast one smoothing range,

[0012] for each pixel of the image, the pixel currently being analysedbeing referred to as the current pixel, the luminance of the said pixelis compared with the said predetermined values delimiting at least onesmoothing range,

[0013] if the luminance of the current pixel lies in one of the saidsmoothing ranges, the luminance of a plurality of pixels, the so-calledanalysis pixels, in a neighbourhood window, the so-called analysiswindow, centred on the current pixel, is compared with the said valuesdelimiting at least one smoothing range,

[0014] if the luminance of at least a predetermined minimum number (n)of analysis pixels lies in the same range as the value of the luminanceof the current pixel, the value of the luminance of the current pixel ismodified as a function of the said threshold values.

[0015] Thus the pixels whose luminance is below a certain threshold aresmoothed. The pixels are not analysed individually, hence betterhomogeneity of smoothing is obtained.

[0016] The term “neighbourhood” is understood to mean the pixelssurrounding the current pixel, currently being analysed. Preferably, thenumber of pixels surrounding the current pixel will comprise about 10pixels (advantageously between 7 and 13 inclusive) in each direction andon each side of the current pixel. The neighbourhood may be both a lineand column or column or line neighbourhood. It will be readilyunderstood that it is simpler to design a line neighbourhood, the numberof points to be traversed and to be stored being restricted in thiscase.

[0017] Moreover, if at least two thresholds are determined, it ispossible to perform progressive smoothing depending on the value of theluminance with respect to the two thresholds. Specifically, if theluminance of the current pixel is below a first threshold, that is tosay if the luminance is relatively low, then it will be possible toapply a smoothing while taking few constraints into account so that thesmoothing is performed as often as possible. If the luminance of thecurrent pixel lies between the two thresholds, that is to say if itsluminance is higher, then it will be possible to apply strongerconstraints so that the correction is made only in vital cases.

[0018] Moreover, a variable stringency is applied to the smoother andthe smoothing is modulated. Specifically, the total luminance scale issplit up into various regions. Thus the pixels whose luminance is low donot undergo the same smoothing as the pixels whose luminance is high.

[0019] According to a particular embodiment, the predetermined so-calledthreshold values are identical to the predetermined values delimiting atleast one smoothing range. Thus the smoothing is made simpler.

[0020] According to a particular characteristic, the process ischaracterized in that the predetermined so-called threshold values areproportional to the noise level of each image. Thus the smoothing takesinto account the particular characteristics of each image.

[0021] Advantageously, the process is characterized in that themodification of the value of the luminance of the current pixel consistsin computing a weighted average of the luminance value of a plurality ofthe K neighbouring pixels, the so-called processing pixels, and of thecurrent pixel and in allocating the value obtained to the luminance ofthe current pixel.

[0022] In this way, the luminance of the smoothed pixel will be inharmony with the value of the luminance of the neighbouring pixels whilelimiting the contrast.

[0023] According to another characteristic, the smoothing ranges are ofdifferent size, the ranges whose luminance is low being wider than thosewhose luminance is high.

[0024] Moreover, the process is characterized in that the predeterminedminimum number of analysis pixels varies as a function of the range inwhich the current pixel is located.

[0025] Thus, according to a particular embodiment, for the rangescomprising pixels of high luminance, it is advantageous for n to behigher than for the ranges whose luminance is low. Specifically, sincethe smoothing is applied only if n pixels are found which belong to therange in the neighbourhood of the current pixel, the more the size ofthe range decreases and the more n increases, hence the less smoothingwill be carried out.

[0026] Advantageously, the modification performed on the value of theluminance of the current pixel is different according to thepredetermined so-called threshold values.

[0027] This has the further advantage of performing a mild smoothing onthe pixels whose luminance is higher and a stronger smoothing on thepixels whose luminance is lower.

[0028] According to a preferred embodiment, the number M of processingpixels used for the weighted average depends on the threshold values (0,S1, S2) between which the luminance of the current pixel lies. In thisway, the size of the processing window used to perform the smoothingvaries and the smoothing can be refined.

[0029] The invention also relates to a device for smoothing dark regionsof an image sequence having undergone temporal filtering, there being anoise level associated with each image, there being a luminance valueassociated with each pixel of an image. The device according to theinvention comprises:

[0030] means for calculating at least one predetermined so-calledthreshold value as a function of the noise level of the image,

[0031] means of determining two predetermined values delimiting at leastone smoothing range,

[0032] means of comparing, for each pixel of the image, the pixelcurrently being analysed being referred to as the current pixel, theluminance of the said pixel with the said predetermined valuesdelimiting at least one smoothing range,

[0033] means of comparison which, if the luminance of the current pixellies in one of the said smoothing ranges, compare the luminance of aplurality of pixels, the so-called analysis pixels, in a neighbourhoodwindow, the so-called analysis window, centred on the current pixel,with the said values delimiting at least one smoothing range,

[0034] means of modifying the value of the luminance of the currentpixel as a function of the said threshold values if the luminance of atleast a predetermined minimum number of analysis pixels lies in the samerange as the value of the luminance of the current pixel,

[0035] the said device being preferably adapted to implement a smoothingprocess as described above.

[0036] The invention also relates to a coding system comprising such asmoothing device.

[0037] The invention will be better understood and other features andadvantages will become apparent on reading the description of theexemplary embodiments which follow, taken by way of nonlimitingexamples, with reference to the appended drawings among which:

[0038]FIG. 1 represents an environment for implementing the deviceaccording to the invention,

[0039]FIG. 2 represents the analysis window used to perform thesmoothing,

[0040]FIG. 3 represents the work window used to perform the smoothing,

[0041]FIG. 4 represents a flowchart for implementing the invention,

[0042]FIG. 5 represents a splitting of the luminance values into threeregions,

[0043]FIG. 6 represents a flowchart of a particular mode of operation ofthe device according to the invention,

[0044]FIG. 7 represents a splitting of the total luminance scale intovarious ranges,

[0045]FIG. 8 represents a flowchart for implementing the inventiontaking into account a splitting of the total luminance scale intovarious ranges.

[0046] The system represented in FIG. 1 represents a noise correctionsystem 1 including a smoothing device 3 or smoother. Such a system isimplemented upstream of a video coder complying with the MPEG standard,the initials standing for “Motion Picture Expert Group”.

[0047] We use the following notation: P current pixel with co-ordinatesx and y, V(P) value of the luminance of the current pixel P, V′(P)modified value of the luminance of the current pixel P, A and Bconstants used for determining the thresholds, σ estimate of the noiselevel, FA analysis window of size 2*K + 1 centred on the current pixel,FA₁ analysis window of size K situated between pixels P − 1 and P − K,FA₂ analysis window of size K situated between pixels P + 1 and P + K,FT processing window, FT₁ processing window used for the stringentsmoothing of size 2M + 1, FT₂ processing window used for the mildsmoothing of size 2M′ + 1, β₁ stringent smoothing coefficient, (|i| <=(FT₁ − 1)/2) α₁ mild smoothing coefficient, (|i| <= (FT₂ − 1)/2)

[0048] Such a system 1 receives as input a noisy image sequence 6. Thisnoisy image sequence enters a temporal recursive filter 2 which may ormay not be motion compensated and also enters a noise level estimator 4.Such a motion compensated temporal filter is described in theapplication EP00401558.2 filed in the name of the company ThomsonLicensing SA.

[0049] This recursive filter produces as a function, among other things,of the estimate of the noise level σ5, a new image sequence 7 whosenoise has been reduced but spread, this representing the unpleasant“dirty window pane” effect on the dark regions of the image.

[0050] In order to eliminate this “dirty window pane” effect thissequence 7 then undergoes smoothing in the device 3. The smoother 3receives as input the noise level σ referenced 5 output by the noiseestimator 4, which is analysed so as to perform the smoothing of thedenoised sequence 7. The noise level σ is associated with an image.

[0051] The smoother 3 outputs a new denoised, but also smoothed,sequence 8. This new image sequence 8 can be injected into the input ofan MPEG type coder.

[0052]FIG. 2 describes an analysis window for the current pixel, as usedin the smoother 3. In order to perform the smoothing, an analysiswindow, also referred to subsequently as a neighbourhood orneighbourhood window of the current pixel, is defined around the currentpixel to be smoothed. This analysis window is centred on the currentpixel. It can be defined in the two directions, horizontal and/orvertical. It is readily understood that for implementational reasons itis simpler to take a horizontal window, that is to say one which takesinto account pixels located on the same line as the current pixel.Specifically, a vertical window and a fortiori a window which takes intoaccount neighbouring columns and lines of the current pixel wouldrequire much more memory room when processing the current pixel since itwould be necessary to read and especially to store many more pixels thanin the case of a horizontal window in order to perform the smoothing.

[0053]FIG. 2 represents a particular embodiment in the case where ahorizontal analysis window FA is chosen. This analysis window is centredon the current pixel P and is broken into two analysis subwindows FA1and FA2 of identical size K. The pixel P has as co-ordinates in theimage, x along a horizontal axis and y along a vertical axis. Theextreme pixels of the analysis window FA therefore have as co-ordinatesx−K and x+K along a horizontal axis and y along a vertical axis.

[0054] The size of the analysis window is chosen reasonably. Thus for aline of 720 pixels it is reasonable to choose a size of analysis windowFA of 15 pixels. In this case, K has the value 7.

[0055]FIG. 3 represents a processing window FT of the smoother 3. Thiswindow is centred on the current pixel P and is broken down into twoprocessing subwindows FT1 and FT2 of identical size M. According to aparticular embodiment, this window is also horizontal, that is to sayall the pixels of this window are situated on the same line of the imageas the current pixel. Specifically, the processing window FT is asubwindow of the analysis window FA. We therefore have M<K.

[0056] The two analysis and processing windows aid the understanding ofFIGS. 4, 6 and 8.

[0057]FIG. 4 describes a first method of smoothing according to theinvention implemented in the smoother 3.

[0058] The smoother 3 calculates at least one threshold S1 with each newimage. This threshold is calculated as a function of the noise level σof the image at the input of the recursive coder 2. This noise level isestimated by the device 4 and transmitted to the recursive coder 2 andto the smoother 3. The threshold is proportional to the noise asfollows:

S1=σ*A, A being a constant.

[0059] In FIG. 4, at step E1, the value of the luminance V(P) of thecurrent pixel is compared with the threshold S1. If this value is abovethe threshold then the value V(P) is not modified and we go to the nextpixel, step E5. If this value is below the threshold then we go to stepE2. In the course of step E2, the value of the luminance of the K pixelsin the analysis window FA1 is compared with the threshold S1. If npixels from among the K pixels have a luminance value below thethreshold, then we go to step E3, otherwise we go to the next pixel,step E5. In the course of step E3, the value of the luminance of the Kpixels in the analysis window FA2 is compared with the threshold S1. Ifn pixels from among the K pixels have a luminance value below thethreshold, then we go to step E4, otherwise we go to the next pixel,step E5. N is preferably greater than K/2. In the course of step E4, thevalue of the luminance of the current pixel is modified according to thefollowing formula (1):${V^{\prime}(P)} = \frac{{\beta_{M}*{V\left( {P - M} \right)}} + {\beta_{M - 1}*{V\left( {P - M + 1} \right)}} + \ldots + {\beta_{0}*{V(P)}} + \ldots + {\beta_{M - 1}*\rho \quad {V\left( {P + M - 1} \right)}} + {\beta_{M}*{V\left( {P + M} \right)}}}{{2*{\sum\limits_{p = i}^{M}\quad \beta_{p}}} + \beta_{0}}$

[0060] The coefficients β_(i) are the weighting coefficients of thefilter. The index i lies between [0, +M].

[0061] In step E5, we go to the next pixel, then we go back to step E1until the entire image has been traversed. When the entire image hasbeen smoothed, we go to the next image and we calculate a new thresholdas a function of the noise level σ of the current image.

[0062]FIG. 5 shows an improvement to the splitting of the totalluminance scale by defining two thresholds S1 and S2. Specifically, theuse of a single threshold simplifies the smoother, but for the pixelswhose luminance is close to the threshold, there is a risk of this beingmanifested visually as a temporal oscillation between the smoothedeffect and non-smoothed effect.

[0063] In a particular embodiment, the smoother 3 calculates twothresholds called S1 and S2. These thresholds are calculated as afunction of the noise level σ of the image at the input of the recursivefilter 2. This noise level is estimated by the device 4 and transmittedto the recursive coder 2 and to the smoother 3. The thresholds areproportional to the noise as follows:

[0064] S1=σ*A

[0065] S2=σ*B with B>A hence S2>S1.

[0066] A and B being constants, the larger A and B are, the more theimage is smoothed since all the pixels whose luminance value is below S1or S2 are smoothed according to the flowchart of FIG. 6 described later.

[0067]FIG. 6 illustrates an embodiment using two thresholds S1 and S2.

[0068] In step F1, the value of the luminance V(P) of the current pixelis compared with the threshold S1. If this value is above the thresholdS1, then we go to step F6. If this value is below the threshold S1, thenwe go to step F2. In the course of step F2, the value of the K pixels inthe analysis window FA1 is compared with the threshold S1. If n pixelsfrom among the K have a luminance value below the threshold S1, then wego to step F3, otherwise we go to the next pixel, step F5. In the courseof step F3, the value of the luminance of the K pixels in the analysiswindow FA2 is compared with the threshold S1. If n pixels from among theK have a luminance value below the threshold S1, then we go to step F4,otherwise we go to the next pixel, step F5. In the course of step F4,the value of the luminance of the current pixel is modified according tothe following formula (1):${V^{\prime}(P)} = \frac{{\beta_{M}*{V\left( {P - M} \right)}} + {\beta_{M - 1}*{V\left( {P - M + 1} \right)}} + \ldots + {\beta_{0}*{V(P)}} + \ldots + {\beta_{M - 1}*{V\left( {P + M - 1} \right)}} + {\beta_{M}*{V\left( {P + M} \right)}}}{{2*{\sum\limits_{p = i}^{M}\quad \beta_{p}}} + \beta_{0}}$

[0069] The coefficients β_(i) are the weighting coefficients of thefilter. The index i lies between [0, +M].

[0070] In step F6, the value of the luminance of the current pixel iscompared with the thresholds S1 and S2. If this value lies between S1and S2 we go to step F7, otherwise we go to step F5. In the course ofstep F7, the value of the luminance of n pixels from among the K in theanalysis window FA1 is compared with the thresholds S1 and S2.

[0071] If n pixels have a luminance value above the threshold S1 andbelow the threshold S2, then we go to step F8, otherwise we go to thenext pixel, step F5. In the course of step F8, the value of theluminance of n pixels in the analysis window FA2 is compared with thethresholds S1 and S2. If n pixels have a luminance value above thethreshold S1 and below the threshold S2, then we go to step F9,otherwise we go to the next pixel, step F5. In the course of step F9,the value of the luminance of the current pixel is modified according tothe following formula (2):${V^{\prime}(P)} = {\frac{\quad {{\alpha_{M^{\prime}}*{V\left( {P - M^{\prime}} \right)}} + {\alpha_{M^{\prime} - 1}*{V\left( {P - M^{\prime} + 1} \right)}} + \ldots + {\alpha_{0}*{V(P)}} + \ldots + {\alpha_{M^{\prime} - i - 1}*{V\left( {P + M^{\prime} - 1} \right)}} + {\alpha_{M^{\prime}}*{V\left( {P + M^{\prime}} \right)}}}}{{2*{\sum\limits_{p = 1}^{M^{\prime}}\quad \alpha_{p}}} + \alpha_{0}}.}$

[0072] M′=(FT2-1)/2, FT2 represents the size of the processing windowand FT2<=FT1.

[0073] The coefficients α_(i) are the weighting coefficients of thefilter. The index i lies between [0, +M′].

[0074] In step F5, we go to the next pixel, then we go back to step F1until the entire image has been traversed. When the entire image hasbeen smoothed, we go to the next image and we calculate new thresholdsas a function of the noise level σ of the current image.

[0075] In FIG. 7, the total luminance scale is broken down into variousranges.

[0076] Specifically, the applicant has noted that the solutionspresented in the two flowcharts of FIGS. 4 and 6 exhibited the advantageof being very simple but could, according to a variant, be moreeffective. Specifically, if the total luminance scale is split intovarious ranges, it is possible to adjust the constraints of applicationof the smoother.

[0077]FIG. 7 shows a breakdown of the total luminance scale into fourranges.

[0078] The ranges whose luminance is low are of larger sizes than theranges whose luminance is high. A high luminance corresponds to a brightregion and a low luminance corresponds to a dark region. The lower theluminance, the weaker the constraints of application of the smootherwill be, that is to say the more the parameter n will change. Thegreater the luminance, the more n will increase, that is to say it willbe necessary for there to be more pixels complying with the applicationcriteria of the filter in the range of the current pixel in order forthe smoothing to be applied.

[0079] Moreover, since the size of the range decreases as the luminanceincreases, it will be more and more difficult to find n pixels in anever narrower range, the filter is thus applied more flexibly in respectof the dark regions than in respect of the bright regions of the image.

[0080] To do this, a certain number (p) of nonuniform ranges ofluminance amplitude are defined:

[0081] a range 1 from 0 to Cst 1

[0082] a range 2 from Cst 1 to Cst 2

[0083] a range 3 from Cst 2 to Cst 3

[0084] . . .

[0085] a range p from Cst (p−1) to Cst p

[0086] (with S2_(max)>Cst p> . . . >Cst 2>Cst 1>0)

[0087] Thus, in FIG. 7 the total luminance scale is split into fourranges for example.

[0088] A first range whose extreme values are 0 and 64. A second rangewhose extreme values are 64 and 112, of size 48. A third range whoseextreme values are 112 and 144 of size 32 and a fourth range whoseextreme values are 144 and 160 of size 16.

[0089] Depending on the range [Cst i, Cst i+1](0<=i<p) in which thevalue V of the luminance of the current pixel is situated, theconditions of application of the smoother are made more or lessstringent. The values of n for the various ranges will for example be asfollows:

[0090] for the range [Cst 0, Cst 1], n=3

[0091] for the range ]Cst 1, Cst 2], n=4

[0092] . . .

[0093] for the range ]Cst p, Cst p+1], n=7

[0094]FIG. 8 gives a flowchart for the operation of this second variantof the invention described in FIG. 7.

[0095] In step G1, the smoother determines the range in which thecurrent pixel is located while smoothing the value of the luminance ofthe current pixel. It thus determines the value of n, the values of nbeing predetermined in the smoother and associated with a range.

[0096] Then, in step G2, the smoother examines the pixels of theanalysis window FA1 and determines whether at least n pixels from amongthe K pixels of the window FA1 belong to the same range as the currentpixel enlarged by 16 pixels (8 above and 8 below). The range is enlargedby 16 pixels, 16 being given by way of indication and so as to deal withthe particular cases where the value of the current pixel is just aboveor below the bounds defining the range. If at least n pixels belong tothe said extended range, then we go to step G3, otherwise we go to stepG8.

[0097] In step G3, the smoother examines the pixels of the analysiswindow FA2 and determines whether at least n pixels from among the Kpixels of the window FA2 belong to the same range as the current pixel,enlarged by 16. If at least n pixels belong to the said extended range,then we go to step G4, otherwise we go to step G8.

[0098] In step G4, the value of the luminance of the current pixel iscompared with the threshold S1. If this value is below or equal to S1,then we go to step G6; otherwise we go to step G5.

[0099] In the course of step G5, the value of the luminance of thecurrent pixel is compared with the thresholds S1 and S2. If thisluminance value is above the threshold S1 and below the threshold S2,then we go to step G7, otherwise we go to the next pixel, step G8. Inthe course of step G6, the value of the luminance of the current pixelis modified according to the following formula (1):${V^{\prime}(P)} = \frac{{\beta_{M}*{V\left( {P - M} \right)}} + {\beta_{M - 1}*{V\left( {P - M + 1} \right)}} + \ldots + {\beta_{0}*{V(P)}} + \ldots + {\beta_{M - 1}*{V\left( {P + M - 1} \right)}} + {\beta_{M}*{V\left( {P + M} \right)}}}{{2*{\sum\limits_{p = i}^{M}\quad \beta_{p}}} + \beta_{0}}$

[0100] The coefficients β_(i) are the weighting coefficients of thefilter. The index i lies between [0, +M].

[0101] In the course of step G7, the value of the luminance of thecurrent pixel is modified according to the following formula (2):${V^{\prime}(P)} = {\frac{\quad {{\alpha_{M^{\prime}}*{V\left( {P - M^{\prime}} \right)}} + {\alpha_{M^{\prime} - 1}*{V\left( {P - M^{\prime} + 1} \right)}} + \ldots + {\alpha_{0}*{V(P)}} + \ldots + {\alpha_{M^{\prime} - i - 1}*{V\left( {P + M^{\prime} - 1} \right)}} + {\alpha_{M^{\prime}}*{V\left( {P + M^{\prime}} \right)}}}}{{2*{\sum\limits_{p = 1}^{M^{\prime}}\quad \alpha_{p}}} + \alpha_{0}}.}$

[0102] M′=(FT2-1)/2, FT2 represents the size of the processing windowand FT2<FT1.

[0103] The coefficients α_(i) are the weighting coefficients of thefilter. The index i lies between [0, +M′].

[0104] In step G8, we go to the next pixel, then we go back to step G1until the entire image has been traversed. When the entire image hasbeen smoothed, we go to the next image and we calculate new thresholdsas a function of the noise level σ of the current image.

1. Process for smoothing dark regions of an image sequence havingundergone temporal filtering, a noise level (σ) being associated witheach image, a luminance value being associated with each pixel of animage, characterized in that, at least one predetermined so-calledthreshold value (S1,S2) is calculated as a function of the noise levelof the image and the zero value is added to the calculated values, atleast two predetermined values (Cst i, Cst i+1) are defined whichdelimit at least one smoothing range, for each pixel of the image, thepixel currently being analysed being referred to as the current pixel(P), the luminance of the said pixel is compared (E1,F1,F6,G1) with thesaid predetermined values (Cst i, Cst i+1) delimiting at least onesmoothing range, if the luminance of the current pixel (P) lies in oneof the said smoothing ranges, the luminance of a plurality (K) ofpixels, the so-called analysis pixels, in a neighbourhood window, theso-called analysis window (FA), centred on the current pixel (P), iscompared (E2,E3,F2,F3,F7,F8,G2,G3) with the said values delimiting atleast one smoothing range, if the luminance of at least a predeterminedminimum number (n) of analysis pixels lies in the same range as thevalue of the luminance of the current pixel, the value of the luminance(V(P)) of the current pixel (P) is modified (E4,F4,F9,G6,F7) as afunction of the said threshold values (0,S1,S2).
 2. Process according toclaim 1, characterized in that the predetermined values (Cst i, Cst i+1)delimiting at least one smoothing range are identical to thepredetermined so-called threshold values (0,S1,S2).
 3. Process accordingto any one of claims 1 or 2, characterized in that the predeterminedcalculated so-called threshold values (S1,S2) are proportional to thenoise level (σ).
 4. Process according to any one of claims 1 to 3,characterized in that the modification (E4,F4,F9,G6,G7) of the value ofthe luminance (V(P)) of the current pixel (P) consists in computing aweighted average of the luminance value of a plurality (M) of the Kneighbouring analysis pixels, the so-called processing pixels, and ofthe current pixel (P) and in allocating the value obtained to theluminance (V(P)) of the current pixel.
 5. Process according to one ofclaims 1 to 4, characterized in that the smoothing ranges are ofdifferent size, the ranges whose luminance is low being wider than thosewhose luminance is high.
 6. Process according to any one of claims 1 to5, characterized in that the predetermined minimum number (n) ofanalysis pixels varies as a function of the range in which the currentpixel is located.
 7. Process according to any one of claims 1 to 6,characterized in that the modification (E4,F4,F9,G6,G7) performed on thevalue of the luminance (V(P)) of the current pixel (P) is differentaccording to the predetermined so-called threshold value(s) (S1,S2). 8.Process according to any one of claims 1 to 7, characterized in that thenumber (M) of processing pixels used for the weighted average depends onthe threshold values (0,S1,S2) between which the luminance of thecurrent pixel lies.
 9. Device (3) for smoothing dark regions of an imagesequence having undergone temporal filtering, a noise level beingassociated with each image, there being a luminance value beingassociated with each pixel of an image, characterized in that itcomprises, means for calculating at least one predetermined so-calledthreshold value (S1,S2) as a function of the noise level of the image,means of determining two predetermined values (Cst i, Cst i+1)delimiting at least one smoothing range, means of comparing, for eachpixel of the image, the pixel currently being analysed being referred toas the current pixel (P), the luminance of the said pixel with the saidpredetermined values (Cst i, Cst i+1) delimiting at least one smoothingrange, means of comparison which, if the luminance of the current pixel(P) lies in one of the said smoothing ranges, compare the luminance of aplurality (K) of pixels, the so-called analysis pixels, in aneighbourhood window, the so-called analysis window (FA), centred on thecurrent pixel (P), with the said values delimiting at least onesmoothing range, means of modifying the value of the luminance (V(P)) ofthe current pixel (P) as a function of the said threshold values(0,S1,S2) if the luminance of at least a predetermined minimum number(n) of analysis pixels lies in the same range as the value of theluminance of the current pixel, the said device being preferably adaptedto implement a smoothing process according to any one of claims 1 to 8.10. Coding system comprising a smoothing device in accordance with claim9.